Dataset Classification Guide

Classify first. Analyze second.

Radiographic datasets are not all alike. RheumaView™ formally classifies every imaging dataset before analysis begins — across temporal structure, anatomy, laterality, modality, and coverage.

i.Eight classification dimensions

The dataset is read before the image is.

Every dataset entering RheumaView™ is described along eight orthogonal axes. These determine which comparisons are valid, which deltas can be computed, and which extractions are trial-compatible.

Dataset classification 01 Temporal Structure Single · Near · Longitudinal 02 Anatomical Domain Spine · Pelvic-SI · Limbs 03 Regional Sets Hand-Wrist · Foot-Ankle · Knee 04 Coverage Pattern Single · Multi · System 05 Symmetry & Laterality Symmetric · Unilateral · Asymmetric 06 Modality Structure Single · Multi-modality 07 Integration Type Pure · Composite · Mixed 08 Standardized Description Unified four-part format

Eight orthogonal dimensions resolved before any structural reading begins.

ii.Case Library index notationRV-### · code
A compact reader-facing label.

Each case in the RheumaView™ Case Library is labeled using a compact index for quick identification. This notation is used throughout the Case Library as a navigation marker. Full dataset classification is defined separately in the broader RheumaView™ classification framework.

Format
RV-[ordinal] · [temporal code]-main class
Example: RV-001 · SP-PER(HW+FA)

RV-[ordinal] — sequential case number
SP / LM / LX — temporal pattern
PER / AX / MIX — main case class
Coverage — abbreviated anatomical regions

Common abbreviations:
SP single time point · LM limited longitudinal · LX extended longitudinal
PER peripheral · AX axial · MIX mixed axial/peripheral
CS cervical · TS thoracic · LS lumbar · SI sacroiliac · PEL pelvis/hips · HW hands/wrists · FA feet/ankles

01Temporal StructureSingle · Near · Longitudinal
Every dataset has a temporal identity.

RheumaView™ recognizes three fundamental temporal types. Misclassification at this layer produces invalid longitudinal comparisons downstream.

Single-Date one examination no internal comparison Near-Temporal Composite days–weeks · same baseline unified structurally Longitudinal Δ Δ matched regions across time quantitative deltas computed TIME temporal identity precedes anatomical reading

Three temporal types — distinguishing baseline composites from genuine longitudinal series.

Single-Date Dataset

All images are acquired on the same examination date. The dataset represents one structural time point, and no internal temporal comparison is possible.

Near-Temporal Composite Dataset (Staged Baseline)

Images are acquired on different dates within a short diagnostic interval — days to several weeks — yet together represent the same structural baseline. RheumaView™ treats such studies as a unified structural baseline rather than as separate longitudinal time points, provided that no clinically meaningful structural change is expected within the interval.

Longitudinal Dataset

Two or more examinations of the same anatomical region obtained at different time points to assess progression, regression, or stability. Regions must match across time points. Quantitative deltas — measured structural differences between matched time points — are computed for each aligned region.

02Anatomical DomainSpine · Pelvic-SI · Limbs
Strict anatomical boundaries.

Regions that are often informally grouped together are treated as distinct analytical units. A cervical vertebra and a sacroiliac joint are not interchangeable data points, even when they appear in the same report.

Spinal Dataset

Cervical, thoracic, and lumbar spine. Does not include sacroiliac joints, pelvis, or hips.

Pelvic–Sacroiliac Dataset

Sacroiliac joints and pelvic bones (ilium, ischium, pubis). Treated as a separate anatomical unit from both the spine and the hips.

Hip Dataset

Right and left hip joints, evaluated independently from pelvic or spinal datasets.

Axial Combined Dataset

Spine and pelvic–sacroiliac components analyzed within the same study while preserving their identities as separate anatomical units.

Upper Extremity Dataset

Shoulders, elbows, wrists, and hands.

Lower Extremity Dataset

Hips, knees, ankles, and feet.

03Regional SetsHand-Wrist · Foot-Ankle · Knee
Clinically linked anatomical groups.

Regional sets represent groups of joints analyzed as a single structural unit, reflecting classical clinical assessment patterns.

Hand–Wrist Set

Wrist joints together with metacarpophalangeal and interphalangeal joints. A classical unit of assessment in inflammatory arthritis.

Foot–Ankle Set

Ankle joints together with metatarsophalangeal and interphalangeal joints.

Knee Set

Tibiofemoral and patellofemoral compartments.

Shoulder Set

Glenohumeral joint and acromioclavicular joint when visible.

04Coverage PatternSingle · Multi · System
How much of the body is represented.

Coverage describes the breadth of anatomical sampling — a property that constrains which inferences about systemic distribution are valid.

Single-Region one anatomical region e.g. bilateral knees Multi-Region two or more regions e.g. hands and feet Regional System full anatomical system e.g. all lower-extremity joints

Coverage scales from focal sampling to full anatomical-system representation.

Single-Region Dataset

One anatomical region only. Example: bilateral knees.

Multi-Region Dataset

Two or more distinct anatomical regions within the same report. Example: hands and feet.

Regional System Dataset

A full anatomical system, typically an entire limb group. Example: all lower-extremity joints.

05Symmetry & LateralitySymmetric · Unilateral · Asymmetric
Side distribution is a structural property.

RheumaView™ classifies datasets not only by region, but also by side distribution. Laterality is not a minor labeling detail; it is a structural property of the dataset and a clinically meaningful analytic variable.

Symmetric Dataset

Bilateral anatomical structures are included. Examples: both hands, both knees, both hips.

Unilateral Dataset

Only one side of a bilateral structure is imaged. Examples: right knee only, left wrist only.

Asymmetric Dataset

Bilateral anatomy is included incompletely or unevenly — one side missing, underrepresented, or not directly comparable to the other.

Many musculoskeletal and rheumatologic disorders carry characteristic side-distribution patterns. A dataset that is unilateral or asymmetric must be classified accordingly before pattern inference begins.

06Modality StructureSingle · Multi-modality
One channel, or many.
Single-Modality Dataset

One imaging modality only: X-ray, MRI, ultrasound, or CT.

Multi-Modality Dataset

Two or more imaging modalities for the same or related regions. Examples: X-ray plus MRI, MRI plus CT, X-ray plus DEXA.

Cross-modality concordance — the degree to which findings from different modalities agree or diverge — is a distinct analytical dimension within RheumaView™. The platform architecture is also designed to support integration with additional diagnostic data streams, including modalities such as EMG/NCS, ultrasound, nuclear imaging, and other structured inputs where relevant. Not all integration pathways are publicly disclosed.

07Dataset Integration TypePure · Composite · Mixed
Pure, composite, or mixed.
Pure Dataset

A single temporal, anatomical, and modality structure with no composite integration. Example: single-date wrist X-ray.

Composite Dataset

Multiple anatomical regions combined within the same time point. Example: hands plus feet X-ray study.

Mixed Dataset

Different temporal or structural types combined within the same analytical session. Example: hand X-ray from one year and sacroiliac MRI from another. Mixed datasets require explicit handling to avoid false longitudinal comparison across incompatible time points or anatomical scopes.

08Standardized Description FormatUnified four-part format
Every case, the same shape.

Every dataset in the RheumaView™ Case Library is described using a consistent four-part structure. This standardized description ensures that every case illustration is unambiguously classified and that comparisons across cases remain meaningful.

[Temporal Structure] + [Anatomical Domain] + [Coverage] + [Modality] Examples:
  • Single-date peripheral multi-region X-ray dataset
  • Near-temporal composite axial radiographic dataset
  • Longitudinal spinal MRI dataset
  • Composite peripheral X-ray dataset
09Output formatsGold · Standard · Concise · Research

This is the condensed framework. The full guide expands every dimension with examples, diagrams, and multilingual versions.

Open the full classification guide →
RheumaView case studies
04 Browse the cases
Clinical + analytical reports Multilingual report availability
  • Combined clinical and analytical reports are available in English, Russian, Spanish, Chinese, Portuguese, German, French, and Italian.
  • Объединенные клинические и аналитические отчеты доступны на английском, русском, испанском, китайском, португальском, немецком, французском и итальянском языках.
  • Los informes clínicos y analíticos combinados están disponibles en inglés, ruso, español, chino, portugués, alemán, francés e italiano.
  • 临床与分析合并报告提供英文、俄文、西班牙文、中文、葡萄牙文、德文、法文和意大利文版本。
  • Os relatórios clínicos e analíticos combinados estão disponíveis em inglês, russo, espanhol, chinês, português, alemão, francês e italiano.
  • Kombinierte klinische und analytische Berichte sind in Englisch, Russisch, Spanisch, Chinesisch, Portugiesisch, Deutsch, Französisch und Italienisch verfügbar.
  • Des rapports cliniques et analytiques combinés sont disponibles en anglais, russe, espagnol, chinois, portugais, allemand, français et italien.
  • I report clinici e analitici combinati sono disponibili in inglese, russo, spagnolo, cinese, portoghese, tedesco, francese e italiano.

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